If we want to take a look at the most prominent AI trends in 2020, then we are back to the idea that computers or programs can both learn and make decisions is a particularly important idea and we must be aware of it, as its operations grow exponentially over time. Because of these two skills, artificial intelligence (AI) systems can now accomplish many tasks that were previously reserved only for humans!
This year has been a busy year for artificial intelligence and machine learning. From leveraging the rapid discovery of drugs to combat the Coronavirus, to chatting software, and from quantum computing to analyzing consumer buying behavior trends, these technologies have helped many industries approach the digital age. Almost every industry imaginable, even retail and healthcare, has benefited from machine learning and other aspects of artificial intelligence.
Even before the global pandemic, companies were turning to the aforementioned technologies to enforce disruption. Thus, despite the horrific epidemic, the effects of AI have not been mitigated. Nevertheless, Covid-19 has played an important role in determining machine learning trends and the most important AI trends in 2020.
In today’s technology driven world, we are all witnessing the amazing growth of AI technology with many new benefits. This revolutionary AI technology is changing the way people live and work.
Now, let’s take an interesting tour of the areas that AI has had a major impact on and learn about the most important AI trends in 2020.
Model Lifecycle Process Platform or ModelOps Algorithm
Artificial Intelligence Trends 2020
While COVID-19 has provided the necessary impetus, many organizations have failed to manage the complex life cycle of machine learning and artificial intelligence models, and this year’s technological trends are more relevant and urgent than before. Opportunities that companies are expected to have years to prepare for are now rapidly becoming a development. To meet these challenges, organizations needed to innovate, invent, and redefine themselves. Because how quickly and responsibly organizations deploy them matters more than ever, too.
We are living in an unprecedented time, heading towards a rapidly changing future. The solution for many companies was to follow the ModelOps approach, which helps define the life cycle of companies and institutions based on prediction and life cycle management of artificial intelligence and decision models, as this curriculum uses AutoAI and DevOps technologies such as continuous integration and continuous deployment (CI / CD) to update models on Regular basis, which gives better business results. It helps companies in more ways than just operating and managing AI models. It allows for scalability, and full accountability for mission-critical activities, or business bottlenecks.
In addition, ModelOps can configure an evaluation model before actually implementing it on production. It can also operate modular training for supervised learning, reinforcement learning, unsupervised learning, deep learning, and robotic process automation. Hence, due to its flexibility and wide usability, it is set to become a big trend in the coming years.
The plethora of programmed robots replacing workers has become the most frequent and powerful picture when we think of artificial intelligence. Robots are already in use today, as many companies are trying to go and rely on robots for various purposes, especially this year because human workers have become the main carrier of COVID-19.
But what’s new is that robots that until now were only used for manual and tedious tasks this year began to do semi-skilled and skilled work as well: fill out forms, create reports, make animations, give instructions, and so on in short. Going from partial automation, we are looking for full automation by training the machines to do the task at hand. For example, in Japan, by 2025, more than 80% of elderly care will be provided by robots, not caregivers!
Not only will this increase efficiency, but it also gives us ample time and energy to focus only on basic tasks that require human intelligence, and this is what makes us consider it one of the most prominent AI trends in 2020.
Customer support and assistance
Every company or organization strives to provide an enjoyable customer experience. Satisfying existing customers helps companies market new products and services. One of the best ways to delight customers is to resolve inquiries and problems as quickly and smoothly as possible. However, it can be difficult for organizations to run well and quickly at the same time, especially when they are expanding. Fortunately, in 2020 more companies are embarking on incorporating artificial intelligence (AI) into their customer support teams to improve relationships.
Moreover, AI is able to assist these teams in ways that were not possible before. It enables companies to improve customer service by providing better response time, interaction, faster responses, stronger customer interaction, and predictive insights. Synthetic system help includes sales and customer services tasks. This has been more streamlined this year.
Predictive analytics and improved personalization
Artificial Intelligence, Neuro-Linguistic Data Processing, and Data Processing Machine Learning have a positive impact on Augmentative Analytics. More companies are starting to use predictive analytics this year. It is essential in customer service, recruitment, price improvement, retail sales, and supply chain optimization. Predictive analytics will help companies use real data to prepare for outcomes and behaviors, and thus be more proactive.
Companies also need to understand delivery services and customer preferences to have an advantage over their competitors. Real-time, comprehensive location data aligns with customer services in online marketplaces. Businesses also need to provide personalized services to stay connected and expand their customer base.
Real-time marketing activities
Artificial Intelligence Marketing uses artificial intelligence techniques to make automated decisions, based on data collection, data analysis, additional audience observations or economic trends that may affect marketing efforts. AI is often used in marketing efforts where speed is essential. Artificial intelligence tools use data and customer profiles to figure out the best way to communicate with customers, then provide them with timely personalized messages “based on real-time algorithms” without interference from members of the marketing team, ensuring maximum efficiency. Artificial intelligence is used to augment marketing teams or to perform more tactical tasks that require fewer human teams.
Modern marketing is based on an in-depth understanding of customer needs and preferences, and hence the ability to act on that knowledge quickly and effectively. The ability to make data-driven decisions in real time has put AI at the forefront of marketing stakeholders. However, this year companies turned to the marketing teams being cautious when deciding the best way to integrate AI into their campaigns and marketing ads. The development and use of artificial intelligence tools is still in its infancy. But real-time data about current marketing decisions is part of real-time marketing. That relies on relevant trends and customer feedback to prepare strategies. As the number of real-time marketing activities increased in 2020, AI led most of it. Besides, more companies will apply artificial intelligence to manage real-time user interactions and customer satisfaction.
Artificial intelligence chatbots (chatbots)